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A network model of affective odor perception.
PloS one
Jul 30, 2020
The affective appraisal of odors is known to depend on their intensity (I), familiarity (F), detection threshold (T), and on the baseline affective state of the observer. However, the exact nature of these relations is still largely unknown. We there...
Modeling motivation for alcohol in humans using traditional and machine learning approaches.
Addiction biology
Jul 29, 2020
Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeking represents a research priority. Prominent addiction theories emphasize the role of motivation in the alcohol seeking process, which has largely bee...
Improving abnormal gait patterns by using a gait exercise assist robot (GEAR) in chronic stroke subjects: A randomized, controlled, pilot trial.
Gait & posture
Jul 29, 2020
BACKGROUND: Although the Gait Exercise Assist Robot (GEAR) has been reported to effectively improve gait of hemiplegic patients, no study has investigated its use in chronic stroke patients. It is possible to facilitate gait reorganization by gait tr...
Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice.
PloS one
Jul 29, 2020
Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine. However, no studies have used artificial neural networks for the prediction...
Experimentally revealed stochastic preferences for multicomponent choice options.
Journal of experimental psychology. Animal learning and cognition
Jul 27, 2020
Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multicomponent c...
Robotic tests for position sense and movement discrimination in the upper limb reveal that they each are highly reproducible but not correlated in healthy individuals.
Journal of neuroengineering and rehabilitation
Jul 25, 2020
BACKGROUND: Robotic technologies for neurological assessment provide sensitive, objective measures of behavioural impairments associated with injuries or disease such as stroke. Previous robotic tasks to assess proprioception typically involve single...
Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS).
Journal of critical care
Jul 24, 2020
PURPOSE: Acute respiratory distress syndrome (ARDS) is a serious respiratory condition with high mortality and associated morbidity. The objective of this study is to develop and evaluate a novel application of gradient boosted tree models trained on...
Depth in convolutional neural networks solves scene segmentation.
PLoS computational biology
Jul 24, 2020
Feed-forward deep convolutional neural networks (DCNNs) are, under specific conditions, matching and even surpassing human performance in object recognition in natural scenes. This performance suggests that the analysis of a loose collection of image...
Reliability of the thumb localizing test and its validity against quantitative measures with a robotic device in patients with hemiparetic stroke.
PloS one
Jul 24, 2020
OBJECTIVES: To examine the inter-rater reliability of the thumb localizing test (TLT) and its validity against quantitative measures of proprioception.
Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort.
BMJ open
Jul 23, 2020
INTRODUCTION: Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at high risk of asthma attacks in primary care by leveraging advances in machine learning.
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